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The database development life cycle
The database development life cycle

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1.6.4 Supporting data management strategies

Most of the development we've covered so far in this course has focused on meeting specific user requirements – that is, ensuring the right data are constrained correctly and made available to the right user processes. However, other questions must also be addressed in order to support a data management strategy: How frequently should data be backed-up? What auditing mechanisms are required? Which users will be permitted to perform which functions? Which database tools and user processes will be available to users to access data? What level of legal reporting is required? And so on. The data administrator will be involved in setting policy, but the implementer needs to ensure that the right data are being accessed in the right ways by the right users, with appropriate security, record keeping and reporting taking place.

Efficiency: the interaction between design and implementation

When using the three-schema architecture we would like to separate the logical schema, that is, the description of the tables in the database, from the storage schema required for its efficient implementation. This separation represents an ideal that is rarely found in a commercial DBMS. This is most evident when we need to take account of efficiency. When DBMSs lack the ability to separate these concerns it forces efficiency issues to be considered during the database design (by choosing efficient table structures) rather than leaving such decisions until the implementation stage. An initial design for a logical schema may be produced, but its efficiency can only be evaluated fully during implementation. If the resulting implemented database is not efficient enough to meet the processing requirements, it is necessary to return to the database design and consider how the logical schema may be changed to be more efficient. If separation of logical and storage schema is possible, and if another storage schema can efficiently implement the logical design, then the logical design may not need revision.

For this reason, some database design methods refer to two separate design stages: logical database design and physical database design. However, this physical stage is mainly concerned with producing a revised logical schema – that is, specifying SQL tables – so this terminology can be confusing. The tables of a logical schema may differ from the relational representation of the conceptual data model because of concerns with efficiency. To make design decisions that address specific efficiency concerns requires detailed knowledge of the specific DBMS facilities and hardware systems that will host the database.